Database Reference
In-Depth Information
12.3 Data Visualization Basics
As the volume of data continues to increase, more vendors and communities are
developing tools to create clear and impactful graphics for use in presentations and
applications. Although not exhaustive,
Table 12.2
lists some popular tools.
Table 12.2
Common Tools for Data Visualization
Open Source Commercial Tools
R (Base package,
lattice
,
ggplot2
) Tableau
GGobi/Rggobi
Spotfire (TIBCO)
Gnuplot
QlikView
Inkscape
Adobe Illustrator
Modest Maps
OpenLayers
Processing
D3.js
Weave
As the volume and complexity of data has grown, users have become more reliant
on using crisp visuals to illustrate key ideas and portray rich data in a simple way.
Over time, the open source community has developed many libraries to offer more
options for portraying graphics data visually. Although this topic showed examples
primarily using the base package of R,
ggplot2
provides additional options for
creating professional-looking data visualization, as does the
lattice
library for R.
Gnuplot and GGobi have a command-line-driven approach to generating data
visualization. The genesis of these tools mainly grew out of scientific computing
and the need to express complex data visually. GGobi also has a variant called
Rggobi that enables users to access the GGobi functionality with the R software
and programming language. There are many open source mapping tools available,
including Modest Maps and OpenLayers, both designed for developers who would
like to create interactive maps and embed them within their own development
projects or on the web. The software programming language development
environment, Processing, employs a Java-like language for developers to create
professional-looking data visualization. Because it is based on a programming
language rather than a GUI, Processing enables developers to create robust
